Ramin Bohlouli is a PhD student at Sapienza University of Rome, focusing on discrete choice analysis and demand prediction in the field of transportation. His research integrates advanced methodologies—including machine learning algorithms and large language models (LLMs)—to enhance mobility systems.
He has a solid background in software development with C# and is also familiar with Python and JavaScript. He is well‐versed in modern software engineering practices such as version control, CI/CD pipelines, and database management using PostgreSQL and MongoDB. His technical expertise is complemented by hands‐on experience with leading transportation engineering tools, including ArcGIS for spatial analysis and PTV Visum and Vissim for traffic simulation and modeling. He combines technical fluency with a strong passion for data‐driven, sustainable transport innovation.